

@misc{brock2016generativediscriminativevoxelmodeling,
      title={Generative and Discriminative Voxel Modeling with Convolutional Neural Networks}, 
      author={Andrew Brock and Theodore Lim and J. M. Ritchie and Nick Weston},
      year={2016},
      eprint={1608.04236},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1608.04236}, 
}


@article{tancik2020fourier,
  title={Fourier features let networks learn high frequency functions in low dimensional domains},
  author={Tancik, Matthew and Srinivasan, Pratul and Mildenhall, Ben and Fridovich-Keil, Sara and Raghavan, Nithin and Singhal, Utkarsh and Ramamoorthi, Ravi and Barron, Jonathan and Ng, Ren},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={7537--7547},
  year={2020}
}



@article{velivckovic2017graph,
  title={Graph attention networks},
  author={Veli{\v{c}}kovi{\'c}, Petar and Cucurull, Guillem and Casanova, Arantxa and Romero, Adriana and Lio, Pietro and Bengio, Yoshua},
  journal={arXiv preprint arXiv:1710.10903},
  year={2017}
}



@inbook{Prabhakar2024,
  title       = {3D Vessel Graph Generation Using Denoising Diffusion},
  booktitle   = {Medical Image Computing and Computer Assisted Intervention – MICCAI 2024},
  publisher   = {Springer Nature Switzerland},
  author      = {Prabhakar, Chinmay and Shit, Suprosanna and Musio, Fabio and Yang, Kaiyuan and Amiranashvili, Tamaz and Paetzold, Johannes C. and Li, Hongwei Bran and Menze, Bjoern},
  year        = {2024},
  pages       = {3--13},
  isbn        = {9783031721205},
  doi         = {10.1007/978-3-031-72120-5_1}
}


@article{Lemeunier2022,
  title     = {Representation learning of 3D meshes using an Autoencoder in the spectral domain},
  author    = {Lemeunier, Cl{\'e}ment and Denis, Florence and Lavou{\'e}, Guillaume and Dupont, Florent},
  journal   = {Computers \& Graphics},
  volume    = {107},
  pages     = {131--143},
  year      = {2022},
  month     = oct,
  doi       = {10.1016/j.cag.2022.07.011}
}


@misc{GraphAF,
  title    = {{GraphAF}: a Flow-based Autoregressive Model for Molecular Graph Generation},
  author   = {Shi, Chence and Xu, Minkai and Zhu, Zhaocheng and Zhang, Weinan and Zhang, Ming and Tang, Jian},
  year     = {2020},
  eprint   = {2001.09382},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi      = {10.48550/arXiv.2001.09382},
  url      = {https://arxiv.org/abs/2001.09382}
}



@inproceedings{DeepGraphGeneration,
  title     = {A Survey on Deep Graph Generation: Methods and Applications},
  author    = {Zhu, Yanqiao and Du, Yuanqi and Wang, Yinkai and Xu, Yichen and Zhang, Jieyu and Liu, Qiang and Wu, Shu},
  booktitle = {Proceedings of the First Learning on Graphs Conference},
  series    = {Proceedings of Machine Learning Research},
  volume    = {198},
  pages     = {47:1--47:21},
  year      = {2022},
  month     = {Dec},
  eprint    = {2203.06714},
  archivePrefix = {arXiv},
  doi       = {10.48550/arXiv.2203.06714}
}

@misc{MeshGPT,
  title    = {{MeshGPT}: Generating Triangle Meshes with Decoder-Only Transformers},
author = {Siddiqui, Yawar and Alliegro, Antonio and Artemov, Alexey and Tommasi, Tatiana and Sirigatti, Daniele and Rosov, Vladislav and Dai, Angela and Nie{\ss}ner, Matthias},
  year     = {2023},
  eprint   = {2311.15475},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi      = {10.48550/arXiv.2311.15475},
  url      = {https://arxiv.org/abs/2311.15475}
}

@misc{LocalDeepImplicit,
  title    = {Local Deep Implicit Functions for 3D Shape},
  author   = {Genova, Kyle and Cole, Forrester and Sud, Avneesh and Sarna, Aaron and Funkhouser, Thomas},
  year     = {2019},
  eprint   = {1912.06126},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi      = {10.48550/arXiv.1912.06126},
  url      = {https://arxiv.org/abs/1912.06126}
}


@misc{GraphiT,
  title    = {{GraphiT}: Encoding Graph Structure in Transformers},
  author   = {Mialon, Gr{\'e}goire and Chen, Dexiong and Selosse, Margot and Mairal, Julien},
  year     = {2021},
  eprint   = {2106.05667},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi      = {10.48550/arXiv.2106.05667},
  url      = {https://arxiv.org/abs/2106.05667}
}

@misc{DominantMotionID,
  title    = {Dominant motion identification of multi-particle system using deep learning from video},
  author   = {Jadhav, Yayati and Farimani, Amir Barati},
  year     = {2021},
  eprint   = {2104.12722},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi      = {10.48550/arXiv.2104.12722},
  url      = {https://arxiv.org/abs/2104.12722}
}

@misc{TrajMAE,
  title    = {{Traj-MAE}: Masked Autoencoders for Trajectory Prediction},
  author   = {Chen, Hao and Wang, Jiaze and Shao, Kun and Liu, Furui and Hao, Jianye and Guan, Chenyong and Chen, Guangyong and Heng, Pheng-Ann},
  year     = {2023},
  eprint   = {2303.06697},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi      = {10.48550/arXiv.2303.06697},
  url      = {https://arxiv.org/abs/2303.06697}
}

@article{TrajVAE,
  title   = {{TrajVAE}: A Variational AutoEncoder model for trajectory generation},
  author  = {Chen, Xinyu and Xu, Jiajie and Zhou, Rui and Chen, Wei and Fang, Junhua and Liu, Chengfei},
  journal = {Neurocomputing},
  volume  = {428},
  pages   = {332--339},
  year    = {2021},
  month   = mar,
  doi     = {10.1016/j.neucom.2020.03.120}
}

@misc{SelfConsistent,
  title    = {Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings},
  author   = {Co-Reyes, John D. and Liu, YuXuan and Gupta, Abhishek and Eysenbach, Benjamin and Abbeel, Pieter and Levine, Sergey},
  year     = {2018},
  eprint   = {1806.02813},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi      = {10.48550/arXiv.1806.02813},
  url      = {https://arxiv.org/abs/1806.02813}
}

@inproceedings{DeepTrajectoryClustering,
  title     = {Deep Trajectory Clustering with Autoencoders},
  author    = {Olive, Xavier and Basora, Luis and Viry, Beno\^{i}t and Alligier, Richard},
  booktitle = {Proceedings of SESAR Innovation Days},
  year      = {2020},
  month     = {Aug},
  url       = {https://enac.hal.science/hal-02916241/document}
}

@misc{BloodVesselGAN,
  title    = {Blood Vessel Geometry Synthesis using Generative Adversarial Networks},
  author   = {Wolterink, Jelmer M. and Leiner, Tim and Isgum, Ivana},
  year     = {2018},
  eprint   = {1804.04381},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi      = {10.48550/arXiv.1804.04381},
  url      = {https://arxiv.org/abs/1804.04381}
}

@misc{VesselVAE,
  title    = {{VesselVAE}: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis},
  author   = {Feldman, Paula and Fainstein, Miguel and Siless, Viviana and Delrieux, Claudio and Iarussi, Emmanuel},
  year     = {2023},
  eprint   = {2307.03592},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi      = {10.48550/arXiv.2307.03592},
  url      = {https://arxiv.org/abs/2307.03592}
}

@misc{MolGAN,
  title    = {{MolGAN}: An implicit generative model for small molecular graphs},
  author   = {De Cao, Nicola and Kipf, Thomas},
  year     = {2018},
  eprint   = {1805.11973},
  archivePrefix = {arXiv},
  primaryClass = {stat.ML},
  doi      = {10.48550/arXiv.1805.11973},
  url      = {https://arxiv.org/abs/1805.11973}
}

@inbook{GraphVAE,
  title     = {{GraphVAE}: Towards Generation of Small Graphs Using Variational Autoencoders},
  author    = {Simonovsky, Martin and Komodakis, Nikos},
  booktitle = {Artificial Neural Networks and Machine Learning -- ICANN 2018},
  pages     = {412--422},
  year      = {2018},
  publisher = {Springer},
  doi       = {10.1007/978-3-030-01418-6_41}
}

@misc{JTVAE,
  title    = {Junction Tree Variational Autoencoder for Molecular Graph Generation},
  author   = {Jin, Wengong and Barzilay, Regina and Jaakkola, Tommi},
  year     = {2018},
  eprint   = {1802.04364},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  doi      = {10.48550/arXiv.1802.04364},
  url      = {https://arxiv.org/abs/1802.04364}
}


@article{VAE_MolecularGraphs,
author = {G{\'o}mez-Bombarelli, Rafael and Wei, Jennifer N. and Duvenaud, David and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel and S{\'a}nchez-Lengeling, Benjam{\'i}n and Sheberla, Dennis and Aguilera-Iparraguirre, Jorge and Hirzel, Timothy D. and Adams, Ryan P. and Aspuru-Guzik, Al{\'a}n},
title = {Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules},
journal = {ACS Central Science},
volume = {4},
number = {2},
pages = {268-276},
year = {2018},
doi = {10.1021/acscentsci.7b00572},
note ={PMID: 29532027}
}


@InProceedings{rajat_deep_structural,
author="Rasal, Rajat
and Castro, Daniel C.
and Pawlowski, Nick
and Glocker, Ben",
editor="Karlinsky, Leonid
and Michaeli, Tomer
and Nishino, Ko",
title="Deep Structural Causal Shape Models",
booktitle="Computer Vision -- ECCV 2022 Workshops",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="400--432",
isbn="978-3-031-25075-0"
}


@inproceedings{kazhdan2006poisson,
  title={Poisson surface reconstruction},
  author={Kazhdan, Michael and Bolitho, Matthew and Hoppe, Hugues},
  booktitle={Proceedings of the fourth Eurographics symposium on Geometry processing},
  volume={7},
  number={4},
  year={2006}
}


@article{SCHNEIDER20121397,
title = {Tissue metabolism driven arterial tree generation},
journal = {Medical Image Analysis},
volume = {16},
number = {7},
pages = {1397-1414},
year = {2012},
note = {Special Issue on the 2011 Conference on Medical Image Computing and Computer Assisted Intervention},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2012.04.009},
url = {https://www.sciencedirect.com/science/article/pii/S1361841512000576},
author = {Matthias Schneider and Johannes Reichold and Bruno Weber and G{\'a}bor Szekely and Sven Hirsch},
keywords = {Arterial tree model, Angiogenesis, Oxygen metabolism, Cerebral vasculature, Computational physiology}
}

@article{liu2023meshdiffusion,
  title={Meshdiffusion: Score-based generative 3d mesh modeling},
  author={Liu, Zhen and Feng, Yao and Black, Michael J and Nowrouzezahrai, Derek and Paull, Liam and Liu, Weiyang},
  journal={arXiv preprint arXiv:2303.08133},
  year={2023}
}

@article{loshchilov2017decoupled,
  title={Decoupled weight decay regularization},
  author={Loshchilov, I},
  journal={arXiv preprint arXiv:1711.05101},
  year={2017}
}

@article{paszke2019pytorch,
  title={Pytorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{ioffe2015batch,
  title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
  author={Ioffe, Sergey},
  journal={arXiv preprint arXiv:1502.03167},
  year={2015}
}

@inproceedings{wu2018group,
  title={Group normalization},
  author={Wu, Yuxin and He, Kaiming},
  booktitle={Proceedings of the European conference on computer vision (ECCV)},
  pages={3--19},
  year={2018}
}

@article{hendrycks2016gaussian,
  title={Gaussian error linear units (gelus)},
  author={Hendrycks, Dan and Gimpel, Kevin},
  journal={arXiv preprint arXiv:1606.08415},
  year={2016}
}

@article{vaswani2017attention,
  title={Attention is all you need},
  author={Vaswani, A},
  journal={Advances in Neural Information Processing Systems},
  year={2017}
}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{radford2018improving,
  title={Improving language understanding by generative pre-training},
  author={Radford, Alec},
  year={2018}
}

@article{locatello2020object,
  title={Object-centric learning with slot attention},
  author={Locatello, Francesco and Weissenborn, Dirk and Unterthiner, Thomas and Mahendran, Aravindh and Heigold, Georg and Uszkoreit, Jakob and Dosovitskiy, Alexey and Kipf, Thomas},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={11525--11538},
  year={2020}
}

@InProceedings{yang2020intra,
  author = {Yang, Xi and Xia, Ding and Kin, Taichi and Igarashi, Takeo},
  title = {IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020}
}

@inproceedings{benbarka2022seeing,
  title={Seeing implicit neural representations as fourier series},
  author={Benbarka, Nuri and H{\"o}fer, Timon and Zell, Andreas and others},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={2041--2050},
  year={2022}
}

@article{sitzmann2020implicit,
  title={Implicit neural representations with periodic activation functions},
  author={Sitzmann, Vincent and Martel, Julien and Bergman, Alexander and Lindell, David and Wetzstein, Gordon},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={7462--7473},
  year={2020}
}